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Journal of Bioinformatics and Computational Biology

Yuriy L Orlov, Tatiana V Tatarinova, Maksim V Zakhartsev, Nikolay A Kolchanov
No abstract text is available yet for this article.
February 13, 2018: Journal of Bioinformatics and Computational Biology
Hossam M Ashtawy, Nihar R Mahapatra
Predicting the native poses of ligands correctly is one of the most important steps towards successful structure-based drug design. Binding affinities (BAs) estimated by traditional scoring functions (SFs) are typically used to score and rank-order poses to select the most promising conformation. This BA-based approach is widely applied and some success has been reported, but it is inconsistent and still far from perfect. The main reason for this is that SFs are trained on experimental BA values of only native poses found in co-crystallized structures of protein-ligand complexes (PLCs)...
February 4, 2018: Journal of Bioinformatics and Computational Biology
George S Krasnov, Nataliya V Melnikova, Valentina A Lakunina, Anastasiya V Snezhkina, Anna V Kudryavtseva, Alexey A Dmitriev
We present MethyMer, a Python-based tool aimed at selecting primers for amplification of complete CpG islands. These regions are difficult in terms of selecting appropriate primers because of their low-complexity, high GC content. Moreover, bisulfite treatment, in fact, leads to the reduction of the 4-letter alphabet (ATGC) to 3-letter one (ATG, except for methylated cytosines), and this also reduces region complexity and increases mispriming potential. MethyMer has a flexible scoring system, which optimizes the balance between various characteristics such as nucleotide composition, thermodynamic features (melting temperature, dimers [Formula: see text]G, etc...
January 30, 2018: Journal of Bioinformatics and Computational Biology
Artem Ryasik, Mikhail Orlov, Evgenia Zykova, Timofei Ermak, Anatoly Sorokin
Predicting promoter activity of DNA fragment is an important task for computational biology. Approaches using physical properties of DNA to predict bacterial promoters have recently gained a lot of attention. To select an adequate set of physical properties for training a classifier, various characteristics of DNA molecule should be taken into consideration. Here, we present a systematic approach that allows us to select less correlated properties for classification by means of both correlation and cophenetic coefficients as well as concordance matrices...
January 30, 2018: Journal of Bioinformatics and Computational Biology
Ivan Antonov, Andrey Marakhonov, Maria Zamkova, Yulia Medvedeva
The discovery of thousands of long noncoding RNAs (lncRNAs) in mammals raises a question about their functionality. It has been shown that some of them are involved in post-transcriptional regulation of other RNAs and form inter-molecular duplexes with their targets. Sequence alignment tools have been used for transcriptome-wide prediction of RNA-RNA interactions. However, such approaches have poor prediction accuracy since they ignore RNA's secondary structure. Application of the thermodynamics-based algorithms to long transcripts is not computationally feasible on a large scale...
January 29, 2018: Journal of Bioinformatics and Computational Biology
Ekaterina Myasnikova, Alexander Spirov
Commonly among the model parameters characterizing complex biological systems are those that do not significantly influence the quality of the fit to experimental data, so-called "sloppy" parameters. The sloppiness can be mathematically expressed through saturating response functions (Hill's, sigmoid) thereby embodying biological mechanisms responsible for the system robustness to external perturbations. However, if a sloppy model is used for the prediction of the system behavior at the altered input (e...
January 25, 2018: Journal of Bioinformatics and Computational Biology
Vladislav Bezhentsev, Sergey Ivanov, Sandeep Kumar, Rajesh Goel, Vladimir Poroikov
Epilepsy is the fourth most common neurological disease after migraine, stroke, and Alzheimer's disease. Approximately one-third of all epilepsy cases are refractory to the existing anticonvulsants. Thus, there is an unmet need for newer antiepileptic drugs (AEDs) to manage refractory epilepsy (RE). Discovery of novel AEDs for the treatment of RE further retards for want of potential pharmacological targets, unavailable due to unclear etiology of this disease. In this regard, network pharmacology as an area of bioinformatics is gaining popularity...
January 24, 2018: Journal of Bioinformatics and Computational Biology
A Ranjitha Dhanasekaran, Katheleen J Gardiner
Reverse Phase Protein Arrays (RPPA) is a high-throughput technology used to profile levels of protein expression. Handling the large datasets generated by RPPA can be facilitated by appropriate software tools. Here, we describe RPPAware, a free and intuitive software suite that was developed specifically for analysis and visualization of RPPA data. RPPAware is a portable tool that requires no installation and was built using Java. Many modules of the tool invoke R to utilize the statistical features. To demonstrate the utility of RPPAware, data generated from screening brain regions of a mouse model of Down syndrome with 62 antibodies were used as a case study...
January 15, 2018: Journal of Bioinformatics and Computational Biology
Alexander M Andrianov, Ivan A Kashyn, Alexander V Tuzikov
An integrated computational approach to in silico drug design was used to identify novel HIV-1 fusion inhibitor scaffolds mimicking broadly neutralizing antibody (bNab) 10E8 targeting the membrane proximal external region (MPER) of the HIV-1 gp41 protein. This computer-based approach included (i) generation of pharmacophore models representing 3D-arrangements of chemical functionalities that make bNAb 10E8 active towards the gp41 MPER segment, (ii) shape and pharmacophore-based identification of the 10E8-mimetic candidates by a web-oriented virtual screening platform pepMMsMIMIC, (iii) high-throughput docking of the identified compounds with the gp41 MPER peptide, and (iv) molecular dynamics simulations of the docked structures followed by binding free energy calculations...
January 15, 2018: Journal of Bioinformatics and Computational Biology
Ekaterina N Grafskaia, Nadezhda F Polina, Vladislav V Babenko, Daria D Kharlampieva, Pavel A Bobrovsky, Valentin A Manuvera, Tatyana E Farafonova, Nikolay A Anikanov, Vassili N Lazarev
As essential conservative component of the innate immune systems of living organisms, antimicrobial peptides (AMPs) could complement pharmaceuticals that increasingly fail to combat various pathogens exhibiting increased resistance to microbial antibiotics. Among the properties of AMPs that suggest their potential as therapeutic agents, diverse peptides in the venoms of various predators demonstrate antimicrobial activity and kill a wide range of microorganisms. To identify potent AMPs, the study reported here involved a transcriptomic profiling of the tentacle secretion of the sea anemone Cnidopus japonicus...
January 3, 2018: Journal of Bioinformatics and Computational Biology
Dmitry Suplatov, Yana Sharapova, Daria Timonina, Kirill Kopylov, Vytas Švedas
The visualCMAT web-server was designed to assist experimental research in the fields of protein/enzyme biochemistry, protein engineering, and drug discovery by providing an intuitive and easy-to-use interface to the analysis of correlated mutations/co-evolving residues. Sequence and structural information describing homologous proteins are used to predict correlated substitutions by the Mutual information-based CMAT approach, classify them into spatially close co-evolving pairs, which either form a direct physical contact or interact with the same ligand (e...
December 28, 2017: Journal of Bioinformatics and Computational Biology
Haixia Dou, Yun Fang, Xiaoqi Zheng
Tumor purity is an intrinsic property of tumor samples and potentially has severe impact on many types of data analysis. We have previously developed a statistical method, InfiniumPurify, which could infer purity of a tumor sample given its tumor type (available in TCGA) or a set of informative CpG (iDMC) sites. However, in many clinical practices, researchers may focus on a specific type of tumor samples that is not included in TCGA, and samples which are too few to identify reliable iDMCs. This greatly restricts the application of InfiniumPurify in cancer research...
December 28, 2017: Journal of Bioinformatics and Computational Biology
Dan Luo, Shu-Lin Wang, Jianwen Fang, Wei Zhang
MicroRNAs (miRNAs) play a key role in gene expression and regulation in various organisms. They control a wide range of biological processes and are involved in several types of cancers by causing mRNA degradation or translational inhibition. However, the functions of most miRNAs and their precise regulatory mechanisms remain elusive. With the accumulation of the expression data of miRNAs and mRNAs, many computational methods have been proposed to predict miRNA-mRNA regulatory relationship. However, most existing methods require the number of modules predefined that may be difficult to determine beforehand...
December 28, 2017: Journal of Bioinformatics and Computational Biology
Vladimir Y Ovchinnikov, Denis V Antonets, Lyudmila F Gulyaeva
MicroRNAs (miRNAs) play important roles in the regulation of gene expression at the post-transcriptional level. Many exogenous compounds or xenobiotics may affect microRNA expression. It is a well-established fact that xenobiotics with planar structure like TCDD, benzo(a)pyrene (BP) can bind aryl hydrocarbon receptor (AhR) followed by its nuclear translocation and transcriptional activation of target genes. Another chemically diverse group of xenobiotics including phenobarbital, DDT, can activate the nuclear receptor CAR and in some cases estrogen receptors ESR1 and ESR2...
December 10, 2017: Journal of Bioinformatics and Computational Biology
Oleg V Vishnevsky, Andrey V Bocharnikov, Nikolay A Kolchanov
The development of chromatin immunoprecipitation sequencing (ChIP-seq) technology has revolutionized the genetic analysis of the basic mechanisms underlying transcription regulation and led to accumulation of information about a huge amount of DNA sequences. There are a lot of web services which are currently available for de novo motif discovery in datasets containing information about DNA/protein binding. An enormous motif diversity makes their finding challenging. In order to avoid the difficulties, researchers use different stochastic approaches...
December 10, 2017: Journal of Bioinformatics and Computational Biology
Jiang Xie, Dongfang Lu, Jiaxin Li, Jiao Wang, Yong Zhang, Yanhui Li, Qing Nie
Many major diseases, including various types of cancer, are increasingly threatening human health. However, the mechanisms of the dynamic processes underlying these diseases remain ambiguous. From the holistic perspective of systems science, complex biological networks can reveal biological phenomena. Changes among networks in different states influence the direction of living organisms. The identification of the kernel differential subgraph (KDS) that leads to drastic changes is critical. The existing studies contribute to the identification of a KDS in networks with the same nodes; however, networks in different states involve the disappearance of some nodes or the appearance of some new nodes...
December 4, 2017: Journal of Bioinformatics and Computational Biology
S Subasri, Santosh Kumar Chaudhary, K Sekar, Manish Kesherwani, D Velmurugan
Fumarase catalyzes the reversible, stereospecific hydration/dehydration of fumarate to L-malate during the Kreb's cycle. In the crystal structure of the tetrameric fumarase, it was found that some of the active site residues S145, T147, N188 G364 and H235 had water-mediated hydrogen bonding interactions with pyromellitic acid and citrate which help to the protonation state for the conversion of fumarate to malate. When His 235 is mutated with Asn (H235N), water-mediated interactions were lost due to the shifting of active site water molecule by 0...
December 2017: Journal of Bioinformatics and Computational Biology
Oliver Eulenstein, Qin Ding, Hisham Al-Mubaid
No abstract text is available yet for this article.
December 2017: Journal of Bioinformatics and Computational Biology
Abolfazl Rezvan, Changiz Eslahchi
A metabolic network model provides a computational framework for studying the metabolism of a cell at the system level. The organization of metabolic networks has been investigated in different studies. One of the organization aspects considered in these studies is the decomposition of a metabolic network. The decompositions produced by different methods are very different and there is no comprehensive evaluation framework to compare the results with each other. In this study, these methods are reviewed and compared in the first place...
December 2017: Journal of Bioinformatics and Computational Biology
Esaie Kuitche, Manuel Lafond, Aïda Ouangraoua
The architecture of eukaryotic coding genes allows the production of several different protein isoforms by genes. Current gene phylogeny reconstruction methods make use of a single protein product per gene, ignoring information on alternative protein isoforms. These methods often lead to inaccurate gene tree reconstructions that require to be corrected before phylogenetic analyses. Here, we propose a new approach for the reconstruction of gene trees and protein trees accounting for alternative protein isoforms...
December 2017: Journal of Bioinformatics and Computational Biology
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